Reading literacy is a fundamental tool in our civilized world today. Reading is essential for practically any career path. Learning how to read at any age is a methodical, step-by-step process, first learning the alphabet followed by sounds and then simple words.The next obvious step is to teach sight words, building vocabulary and fluency. Finally, every successful reader must have reading comprehension to use the information gathered in the reading process.
In a recent Salient blog, Data, Data Everywhere and not a Drop to Drink, I talked about the abundance of data that is almost overwhelming in the workplace. Yet the availability of data does not necessarily mean that the data is useful to decision makers. Data literacy, just like reading literacy, is increasingly important so that those connecting with data for analysis know how to read the data. Fluency in any language is the methodical step-by-step process that we all learned in the first grade.
Derek Lyons noted in a recent Business Wire piece that an escalating skills gap is appearing in the workforce, interfering with a full and strategic use of data. While many analysts maintain a high level of technical proficiency, they may lack subject-matter expertise, inhibiting their data literacy. As a result, workers may lack the skills to manage the abundance of data sufficiently in order to create usable insights.
Fortunately, performance improvement and data analytic tools like Salient Dashboards and Salient Interactive Miner make it easier for a nontechnical person to access and analyze complex healthcare data. Point and click technology coupled with rapid data access is eliminating the cumbersome “inquiry writing” that required technical language skills and often took hours or even days to generate a response.
Now with drillable dashboards, the subject-matter user can drill down into the data following their natural curiosity. Additionally, the same user can export their curiosity to Salient Interactive Miner, a deeply analytic tool where there is the opportunity to literally get lost in the data. Yet the language is still understandable.
While it is true that there may be increasing data illiteracy, modern technology is making it easier for Johnny to read. He does not need highly-tuned technical language or understanding because he can now read in his natural subject-matter language. Salient’s performance improvement and analytical tools are also creating opportunities for Dick, Jane, and Sally to become full participants in the analytical economy, leaving some time to play with Spot.
Run Spot run!
